Volume 23, Issue 2

This paper proposes a security-constrained single and multi-objective optimization (MOO) based realistic security constrained-reactive power market clearing (SC-RPMC) mechanism in a hybrid power system by integrating the wind energy generators (WEGs) along with traditional thermal generating stations. Pre-contingency and post-contingency reactive power price clearing plans are developed. Different objective functions considered are the reactive power cost (RPC) minimization, voltage stability enhancement index (VSEI) minimization, system loss minimization (SLM), and the amount of load served maximization (LSM). These objectives of the SC-RPMC problem are solved in a single objective as well as multi-objective manner. The choice of objective functions for the MOO model depends on the load model and the operating condition of the system. For example, the SLM is an important objective function for the constant power load model, whereas the LSM is for the voltage-dependent/variable load model. The VSEI objective should be used only in near-critical loading conditions. The SLM/LSM objective is for all other operating conditions. The reason for using multiple objectives instead of a single objective and the rationale for the choice of the appropriate objectives for a given situation is explained. In this work, the teaching learning-based optimization (TLBO) algorithm is used for solving the proposed single objective-based SC-RPMC problem, and a non-dominated sorting-based TLBO technique is used for solving the multi-objective-based SC-RPMC problem. The fuzzy decision-making approach is applied for extracting the best-compromised solution. The validity and efficiency of the proposed market-clearing approach have been tested on IEEE 30 bus network.

This paper presents a new active power loss allocation (LA) scheme for fair allocation of losses among the end-user with due consideration to deregulation in power supply. In this deregulated environment, the developed technique assigns losses judiciously because it has simplified the difficulties lying with the division of cross-term power loss equation analytically without any assumptions and approximations. Further, it establishes a direct relationship between two end-voltages of a branch and its subsequent load currents, in terms of node-injected complex powers. This LA scheme assigns losses to the network participants with due consideration to their demands, power factors, and geographical locations in the network. Again, the strategy followed for remuneration of distributed generators (DGs) awards all benefits of network loss reduction (NLR) to the DG owners in terms of incentives/penalties after analyzing their actual impact towards system loss reduction. The effectiveness of the proposed method is not only investigated at different load levels but also with various types of DG power injection using a 33-bus radial distribution network (RDN) with/without DGs. The comparison results obtained signify the novelty of the present technique in contrast to other discussed established methods.

Reactive power sharing continues to be a challenge for an autonomous Microgrid (MG) since reactive power sharing is largely affected by the mismatch in line impedance and the asymmetry of local loads. Several reactive power sharing methods have been proposed in an autonomous MG but their effectiveness on large MG systems has not been explored much. This paper considers a standard IEEE 38 bus autonomous MG to study the effectiveness of proportionate power sharing. A simple network reduction technique has been proposed to obtain an equivalent reduced MG for which a reactive power sharing technique is applied. The most feasible method has been analyzed and the communication based reactive power sharing along with droop controller is proved to be the popular and most generalized strategy for effective power sharing. MATLAB-Simulink tool is used to validate the power sharing with equal and unequal DG ratings in a standard IEEE 38 bus autonomous MG system with network reduction.

A four-switch inverter called the B4 inverter is a reconfigured topology of a B6 inverter, one leg of which is damaged. The four-switch topology provides the overall system with fault-tolerant characteristics. However, this reconfiguration will not only change the system dynamics but also degrade the system performance. For overcoming with these issues, this paper presents an adaptive switching method based on DC-link voltage control. In the proposed method, the selection of active vectors and the calculation of switching times are made according to an adaptive, observer-based algorithm which will reduce DC-link voltage oscillations and adjust unbalanced currents fed to induction machines. In this algorithm, an online, designed observer is utilized so as to estimate the DC amount of the DC-link voltage. Applying this method, we will decrease flux and torque ripples as well as increase the inverter efficiency and performance. The simulation results presented in the MATLAB environment evaluate and validate the performance and effectiveness of this approach.

Short-term load forecasting (STLF) is very important for an efficient operation of the power system because the exact and stable load forecasting brings good results to the power system. This manuscript presents the application of two new models in STLF i.e. Cross multi-models and second decision mechanism and Residential load forecasting in smart grid using deep neural network models. In the cross multi-model and second decision mechanism method, the horizontal and longitudinal load characteristics are useful for the construction of the model with the calculation of the total load. The dataset for this model is considered from Maine in New England, Singapore, and New South Wales of Australia. While, In the residential load forecasting method, the Spatio-temporal correlation technique is used for the construction of the iterative ResBlock and deep neural network which helps to give the characteristics of residential load with the use of a publicly available Redd dataset. The performances of the proposed models are calculated by the Root Mean Square Error, Mean Absolute Error, and Mean Absolute Percentage Error. From the simulation results, it is concluded that the performance of cross multi-model and second decision mechanism is good as compare to the residential load forecasting.

The increasing use of power electronics devices as well as the integration of renewable source-based microgrids (MG) has seriously affects the power quality (PQ) of the three-phase power system. Therefore, for the improvement of PQ, it is required to reduce the total harmonics distortion (THD) in the utility network. In this work, the improvement of PQ is discussed in a photovoltaic (PV) based MG integrated three-phase system using a three-level H-bridge (3LHB) multilevel inverter (MI). The MI is used for compensating the source current harmonics and reducing the THD by meeting the IEEE standard guidelines. Besides, the proposed model helps manage the reactive power with control of DC link bus voltage through the PV system. The proposed model is helpful not only in reducing the harmonics but also in providing additional active power to the load if any electrical disturbances occur on the grid side. The maximum power point tracking (MPPT) technique employed in PV is of an improved form of Perturb and Observe (P&O). Further, the reference current generation is derived using the direct current control (DCC) and indirect current control (ICC) techniques. The MG integrated MI is investigated in both DCC and ICC method using three different DC bus voltage controllers; proportional-integral (PI), fuzzy logic controller (FLC), and fuzzy sliding mode control (FSMC). The proposed microgrid integrated system is analyzed with the MATLAB/Simulink tool.

Renewable energy growing is considered one of the main sources of the system harmonics. Thus, in this paper, Total Harmonic Distortion (THD) is reduced by using flexible AC transmission systems (FACTs). Static Compensator (STATCOM) and Static Synchronous Series Compensator (SSSC) are used and compared against basic harmonics filter. Cases studied are as follows: First, the system is studied without any harmonic limitation. Then each type of the chosen two types of (FACTs) is connected to the system. Finally, the harmonics filter is used as a reference to verify the (FACTs) effectiveness. MATLAB/SIMULINK is the tool to examine and simulate the system.

Today, the expansion of power sources is the main task to meet the development of demand. Therefore, Da Nang City has been approved to build the Khanh Son waste incineration power plant in the near future. The Khanh Son power plant project not only helps to reduce a large amount of waste in the area but also provides electricity supply directly to the city, increasing the budget for that locality. However, the connection of this power plant to the system will modify the operating parameters of the grid which may cause some negative impact on the regional power system. Therefore, the main aim of this paper is to simulate various operation modes of the system such as steady-state mode, short circuits, and transient to evaluate the impact of the connection of the new power plant on the national power. The result shows that the Khanh Son power plant helps to reduce the overload of the main cable during the high load scenario, the stability of the system is enhanced significantly. Based on the simulation results, some recommendations to ensure the stabilizing of the grid have been proposed as well.

At present, due to the increase and significant complication of the electric power system (EPS), the task of maintaining the stability of the EPS is becoming increasingly important. Due to the fact that, in case of significant disturbances in the EPS, the processes occurring can lead to large synchronous swings of the generating equipment or loss of stability. When disconnecting the intersystem communication or a powerful load in the excess part of the EPS, an emergency excess of generated active power occurs, as a result, the frequency begins to increase, and the load-frequency control system is not able to cope with such an accident, due to its slowness. In this case, it is necessary to use the means of emergency automation to eliminate the surplus of active power. One of the most effective methods is fast valving automation. However, its effectiveness directly depends on the quality of its setting - which is a rather difficult task, since for its implementation, a complete mathematical model of the turbo-generator is required, taking into account its control systems and boiler unit.

Enhancement of Dielectric strength is an important issue to enhance power system reliability. Insulation filling such as Alumina Trihydrate (ATH) and Silicon dioxide (Sio 2 ) are used to enhance the dielectric strength of polymer insulator. The paper proposes a mathematical model of dielectric strength considering different temperatures and filling percentages using neural network. Moreover, comparison of filling materials is carried out through this model. The comparison shows the superiority of ATH in enhancing the dielectric strength of the polymer. Also, the obtained model will help in getting the best filling concentration without needing to repeat the tests which can be considered as a techno-economical solution to enhance the dielectric strength. Finally, the curve fitting is used to get the dielectric strength model not only as a function of filling concentration percentage but also as a function of temperature.

China has set a new goal of reaching carbon peak by 2030 and becoming carbon neutralization by 2060. To achieve this goal as well as provide a strong and reliable energy supply for comprehensive revitalization of Northeast China, special action is planning by Northeast China power grid (NCPG). Current situation of renewable energy in NCPG is introduced at first. As the primary method for renewable energy accommodation in Northeast China, the existing rules of ancillary services (AS) market are then analyzed. However, considering the rapid growth of renewable energy installed capacity, the existing market has some limitations. In this paper, we take the structural reform on generation side as thread and market demand as guidance. Initiatives and suggestions for high quality development of renewable energy in Northeast China are then proposed for each implementation stage. Through the improving of market rules, expansion of market scale and cultivation of new market entities, NCPG may realize full consumption of the generated renewable energy. The transition from generation side upgrade to the aggregation of source and storage and finally to the cooperation of source-grid-load-storage will be facilitated and accelerated.

Renewable energy-based smart grids are famous nowadays due to their high intellectual properties. The world is starting new inventions in renewable energy-based electrical power generation systems to reduce global warming. However, a single renewable energy source cannot maintain a proper energy management system and reliability of power towards loads. Hence, integrating two or more systems is very important and can form a smart grid with an appropriate energy management system. Effective energy management system for a 4-wire 1-MW smart grid system is proposed in this paper. The system is composed of three solar plants and three wind farms with a battery bank. The battery energy management system can operate the complete system as a smart grid with the proper design of the controllers. The maximum power points of PV plants are tracked using a hybrid algorithm that merges the merits of Modified Invasive Weed Optimization and Perturb and Observe (P&O). Thus, the maximum power is obtained under partial shading conditions. The P&O algorithm is also developed to track the maximum power of wind farms. All the loads and generation units are connected in a ring-configuration distribution with a centralized battery energy management system. The loads are selected to be unbalanced, nonlinear and reactive to simulate practical cases. TS-Fuzzy based common inverter controller is implemented to maintain acceptable power quality, which is linked to the battery. The proposed inverter controller can work as a reactive power compensator, active power filter, voltage regulator under unbalanced load, and power balancing device between generation and load. Extensive Hardware-in-Loop (HIL) results are presented to validate the effectiveness of the proposed system.